# Machine Learning Engineer - Foundational at Harmattan AI

Machine Learning Engineer - Foundational at Harmattan AI in Zurich. On-site, full-time. Posted June 18, 2026.

- Company: Harmattan AI
- Location: Zurich
- Workplace: On-site
- Job type: Full-time
- Experience: 5+ years
- Posted: 2026-06-18
- Apply: https://jobs.ashbyhq.com/harmattan-ai/4e63d35a-935f-4f1d-9076-5a75a7f50ea9/application
- Source: https://jobmagic.ai/jobs/machine-learning-engineer-foundational-harmattan-ai-1swhb7

## Requirements

- Educational Background: A PhD or a highly research-focused MS in Computer Science, Machine Learning, Computer Vision, or Applied Mathematics.
- Proven Experience: Minimum of 5-6 years of experience for senior levels. Experience training and scaling deep learning vision models (ViTs, CNNs) from scratch in multi-GPU/multi-node environments. Successful application of novel SSL or multi-modal architectures (e.g., CLIP, MAE, DINO) to real-world, non-standard imaging data (IR, SAR, or hyperspectral).
- Technical Proficiency: Hardcore PyTorch engineering skills combined with deep mathematical intuition for representation learning. Knowledge of system-level languages (C++, Rust, or Go) and resource optimisation for edge computing.
- Complexity & Leadership: Ability to architect state machines for fault-tolerant data pipelines and mediate technical trade-offs between hardware and algorithm teams.
- Commitment & Mindset: 100% dedication to Harmattan AI’s mission of providing an ethical defence edge to allied countries. A hybrid researcher-engineer mindset that treats data quality as seriously as algorithm design

## Description

### **About Us**

Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.
Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.

### About the Role

As a Machine Learning Engineer on our Foundational team in Paris, you will build the "brain" of our tactical robots. You will design and scale large-scale, multi-modal foundational models that learn robust representations of the battlefield using Self-Supervised Learning (SSL) from massive amounts of unlabelled Electro-Optical (EO) and Infrared (IR) data. Your work provides the critical foundational weights that our Edge AI team distills into hyper-accurate models running on tactical hardware.
 

### Responsibilities

- **Multi-Modal SSL Architecture Design:** Design neural network architectures (Vision Transformers) and loss functions (Masked Autoencoders, Contrastive Learning) to jointly learn from paired and unpaired EO and IR data.

- **Distributed Training Infrastructure:** Manage and optimise training pipelines across multi-node GPU clusters, handling mixed-precision training and data loading.

- **Representation Evaluation:** Develop metrics and linear-probing benchmarks to prove the latent space captures useful semantic features before distillation.

- **Data Strategy:** Audit existing EO/IR data lakes and implement cross-attention mechanisms to fuse diverse sensor features.

- **Cross-Functional Collaboration:** Sync with Data Engineers on ingestion pipelines and collaborate with the Edge AI team to ensure high-performance model handoffs.

**Candidate Requirements**

- **Educational Background:** A PhD or a highly research-focused MS in Computer Science, Machine Learning, Computer Vision, or Applied Mathematics.

- **Proven Experience:** Minimum of 5-6 years of experience for senior levels. Experience training and scaling deep learning vision models (ViTs, CNNs) from scratch in multi-GPU/multi-node environments. Successful application of novel SSL or multi-modal architectures (e.g., CLIP, MAE, DINO) to real-world, non-standard imaging data (IR, SAR, or hyperspectral).

- **Technical Proficiency:** Hardcore PyTorch engineering skills combined with deep mathematical intuition for representation learning. Knowledge of system-level languages (C++, Rust, or Go) and resource optimisation for edge computing.

- **Complexity & Leadership:** Ability to architect state machines for fault-tolerant data pipelines and mediate technical trade-offs between hardware and algorithm teams.

- **Commitment & Mindset:** 100% dedication to Harmattan AI’s mission of providing an ethical defence edge to allied countries. A hybrid researcher-engineer mindset that treats data quality as seriously as algorithm design

We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.